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Analysis of genotype by methylation interactions through sparsity-inducing regularized regression
In this paper, we consider the use of the least absolute shrinkage and selection operator (LASSO)-type regression techniques to detect important genetic or epigenetic loci in genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS). We demonstrate how these techniques can...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157158/ https://www.ncbi.nlm.nih.gov/pubmed/30275890 http://dx.doi.org/10.1186/s12919-018-0145-6 |
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author | Zhou, Wenda Lo, Shaw-Hwa |
author_facet | Zhou, Wenda Lo, Shaw-Hwa |
author_sort | Zhou, Wenda |
collection | PubMed |
description | In this paper, we consider the use of the least absolute shrinkage and selection operator (LASSO)-type regression techniques to detect important genetic or epigenetic loci in genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS). We demonstrate how these techniques can be adapted to provide quantifiable uncertainty using stability selection, including explicit control of the family-wise error rate. We also consider variants of the LASSO, such as the group LASSO, to study genetic and epigenetic interactions. We use these techniques to reproduce some existing results on the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) data set, which collects from 991 individuals blood triglyceride and differential methylation at 464,000 cytosine-phosphate-guanine (CpG) sites and 761,000 single-nucleotide polymorphisms (SNPs), and to identify new research directions. Epigenome-wide and genome-wide models based on the LASSO are considered, as well as an interaction model limited to chromosome 11. The analyses replicate findings concerning 2 CpGs in carnitine palmitoyltransferase 1A (CPT1A). Some suggestions are made regarding potentially interesting directions for the analysis of genetic and epigenetic interactions. |
format | Online Article Text |
id | pubmed-6157158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61571582018-10-01 Analysis of genotype by methylation interactions through sparsity-inducing regularized regression Zhou, Wenda Lo, Shaw-Hwa BMC Proc Proceedings In this paper, we consider the use of the least absolute shrinkage and selection operator (LASSO)-type regression techniques to detect important genetic or epigenetic loci in genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS). We demonstrate how these techniques can be adapted to provide quantifiable uncertainty using stability selection, including explicit control of the family-wise error rate. We also consider variants of the LASSO, such as the group LASSO, to study genetic and epigenetic interactions. We use these techniques to reproduce some existing results on the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) data set, which collects from 991 individuals blood triglyceride and differential methylation at 464,000 cytosine-phosphate-guanine (CpG) sites and 761,000 single-nucleotide polymorphisms (SNPs), and to identify new research directions. Epigenome-wide and genome-wide models based on the LASSO are considered, as well as an interaction model limited to chromosome 11. The analyses replicate findings concerning 2 CpGs in carnitine palmitoyltransferase 1A (CPT1A). Some suggestions are made regarding potentially interesting directions for the analysis of genetic and epigenetic interactions. BioMed Central 2018-09-17 /pmc/articles/PMC6157158/ /pubmed/30275890 http://dx.doi.org/10.1186/s12919-018-0145-6 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Proceedings Zhou, Wenda Lo, Shaw-Hwa Analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
title | Analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
title_full | Analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
title_fullStr | Analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
title_full_unstemmed | Analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
title_short | Analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
title_sort | analysis of genotype by methylation interactions through sparsity-inducing regularized regression |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157158/ https://www.ncbi.nlm.nih.gov/pubmed/30275890 http://dx.doi.org/10.1186/s12919-018-0145-6 |
work_keys_str_mv | AT zhouwenda analysisofgenotypebymethylationinteractionsthroughsparsityinducingregularizedregression AT loshawhwa analysisofgenotypebymethylationinteractionsthroughsparsityinducingregularizedregression |